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100% fundable

Architecting with Google Kubernetes Engine

Running Kubernetes on Google Cloud is more than deploying clusters – it means designing architectures that scale, handle failures, and support automated delivery pipelines.

Key topics

  • Designing, configuring, and operating Kubernetes clusters
  • Orchestrating containers in Google Cloud environments
  • Workload deployment and security hardening in production GKE environments
  • Network design and security architecture on Google Kubernetes Engine
  • CI/CD integration and automated deployment strategies
  • Horizontal and vertical scaling and high availability
  • Monitoring, logging, and observability concepts in GKE
  • Connecting and using cloud-native Google services

Prerequisite
A background in Linux, IT infrastructure, and cloud fundamentals is required. Prior exposure to container technologies is beneficial.

Target group
Architects, engineers, and system administrators who want to design and operate containerised applications on Google Cloud in production environments.

GKE provides a powerful foundation for running scalable, highly available applications. Mastering architecture on Google Kubernetes Engine creates the conditions for reliable and efficient cloud platforms.

Course Content
  • Working with the Google Cloud Console
  • Getting started with Cloud Shell
  • Cloud computing fundamentals
  • Overview of Google Cloud Compute services
  • Regions and zones in Google Cloud
  • Resource hierarchy in Google Cloud
  • Managing Google Cloud resources
  • Building containers with Cloud Build
  • Storing container images in the Container Registry
  • Relationship between Kubernetes and Google Kubernetes Engine (GKE)
  • Choosing the right Google Cloud Compute platform
  • Kubernetes architecture in overview: Pods and Namespaces
  • Control Plane components in Kubernetes
  • Building container images with Cloud Build
  • Storing images in the Container Registry
  • Setting up a Kubernetes Engine cluster
  • kubectl – the central command
  • Practical use of kubectl
  • Analysing clusters and pods
  • Accessing pod logs and console output
  • Interactive access to pods
  • Deployment concepts
  • Approaches to creating deployments
  • Service configuration and scaling
  • Updating deployments
  • Rolling update strategies
  • Blue/Green deployment patterns
  • Canary deployment patterns
  • Deployment management
  • Kubernetes Jobs and CronJobs
  • Parallelised job execution
  • Scheduled CronJobs
  • Cluster autoscaling
  • Scale-down strategies
  • Node pool configuration
  • Pod placement management
  • Affinity and anti-affinity rules
  • Practical example: pod scheduling
  • Taints and tolerations in Kubernetes
  • Software deployment in Kubernetes clusters
  • GKE network architecture fundamentals
  • Pod network communication
  • Kubernetes Services
  • Service discovery in Kubernetes
  • Service types and load balancing
  • Load balancer mechanisms
  • Ingress configuration
  • Container-native load balancing
  • Network security in GKE
  • Kubernetes Volumes
  • Types of Volumes
  • PersistentVolume concept
  • PersistentVolumes in detail
  • StatefulSets for stateful applications
  • Configuration management with ConfigMaps
  • Managing Secrets securely
  • Kubernetes authentication and authorisation concepts
  • Configuring RBAC roles and role bindings for namespace resources
  • Setting up ClusterRoles and ClusterRole bindings for cluster-wide resources
  • Defining pod security policies
  • IAM structure in Google Cloud
  • Setting IAM roles and policies for GKE cluster administration
  • Observing availability and performance with Cloud Monitoring
  • Analysing Kubernetes logs
  • Setting up health-check probes for live applications
  • Managed vs. self-managed storage – advantages and trade-offs
  • Connecting GKE applications to Google Cloud storage services
  • Use cases for Cloud Storage, Cloud SQL, Cloud Spanner, Cloud Bigtable, and Cloud Firestore in Kubernetes
  • BigQuery integration in Kubernetes applications
  • CI/CD fundamentals
  • CI/CD strategies for GKE
  • Practical CI/CD examples

Up to 100% funding for your continuing education

Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.

Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.

Frequently asked questions

  • Building, scaling, and operating Kubernetes workloads on Google Cloud – with hands-on exercises covering real deployment and cluster scenarios.
  • GKE handles Kubernetes management automatically, reduces operational overhead, and enables faster-scaling cloud applications.
  • The course uses GKE, Kubernetes, Docker, CI/CD pipelines, and cloud monitoring tools for production-close container environments.
  • Particularly suited to cloud engineers, DevOps teams, and IT architects building scalable infrastructure and modern cloud platforms.
  • GKE addresses automated deployments, load balancing, high availability, and efficient scaling of container-based applications.
  • Participants gain architectural principles, cluster concepts, and field-tested workflows for stable, production-ready GKE environments.
  • Accelerated deployment, optimised resource utilisation, and simplified management of complex microservice landscapes.
  • Container-based infrastructures are an established part of modern cloud environments – Kubernetes skills are more in demand than ever for IT and DevOps roles.

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